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import gradio as gr |
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from fastai.vision.all import load_learner, PILImage |
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learn = load_learner('export.pkl') |
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labels = learn.dls.vocab |
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def predict(img): |
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img = PILImage.create(img) |
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pred,pred_idx,probs = learn.predict(img) |
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return {labels[i]: float(probs[i]) for i in range(len(labels))} |
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title = "Bear Classifier" |
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description = "A prototype bear classifier developed with fastaiwith images from ddg. Created as a demo for Gradio and HuggingFace Spaces." |
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examples = [r'examples/grizzly_bear.jpg'] |
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demo = gr.Interface(fn=predict, inputs="image", outputs="label") |
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demo.launch() |